# -*- coding: utf-8 -*-

import cv2
import numpy as np
img = cv2.imread('./img/temp/1501598298221.jpg')
# 把图片转换为单通道的灰度图
gray_img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
# 获取形状以及长宽
img_shape = gray_img.shape
height, width = img_shape[0], img_shape[1]
size = gray_img.size
# 灰度图的直方图
hist = cv2.calcHist([gray_img], [0], None, [256], [0, 256])
# 计算灰度图像素点偏离均值(128)程序
a = 0
ma = 0
#np.full 构造一个数组，用指定值填充其元素
reduce_matrix = np.full((height, width), 128)
shift_value = gray_img - reduce_matrix
shift_sum = np.sum(shift_value)
da = shift_sum / size
# 计算偏离128的平均偏差
for i in range(256):
    ma += (abs(i-128-da) * hist[i])
m = abs(ma / size)
# 亮度系数
k = abs(da) / m
print(k,da)
if k[0] > 1:
    # 过亮
    if da > 0:
        print("过亮")
    else:
        print("过暗")
else:
    print("亮度正常")